1. Field of the Invention
The present invention relates to systems and methods for automatic facial recognition, including one-to-one and one-to-many correlations. More particularly, it relates to a system for correcting pose or lighting prior to determining recognition.
2. Discussion of Related Art
Automated facial recognition systems, used to identify individuals from images of faces, have existed for some time. There are several different types of facial recognition systems. In all such systems, a newly acquired image is compared to one or more stored images. Generally, facial recognition systems can be separated into two categories: authentication systems and identification system.
Authentication systems are used to verify the identity of a specific individual, typically to provide access to various resources. For example, an authentication system may use facial recognition to determine whether the individual should be allowed to enter various secured locations or resources, such as computer files, programs, etc. In an authentication system, a image is acquired of the person to be identified. The image is compared to a single image from a database of persons who are permitted access. The single image for comparison is determined based upon additional identifying information in the database, such as a name. In authentication systems, it is important to prevent access by unauthorized persons. The system needs to be able to determine a match with a very high degree of precision in order to preclude people with makeup or disguises.
Identification systems are used to identify an unknown individual by comparing a specific image to multiple images in a database. For example, an image from a security camera may be compared to a database of known criminals to seek to identify the perpetrator of a crime. The image is compared to all of the images in the database to determine one or more closest matches. While the precision of the match is not as important as in authentication systems, and identification system needs to be able to recognize the true identity of a person who may be trying to hide his or her features.
In both authentication systems and identification systems, the images are processed in various ways to determine matches. In some systems, the images are analyzed to locate specific facial features. The relative locations of the facial features are compared to determine a match. In other systems, the entire image is analyzed to determine relationships between light and dark areas in the image. In any type of facial identification system, variations in the conditions under which an image is acquired can affect the characteristics of an image and the ability of the system to determine matches. For example, differences in lighting change the shadowing on the face and the associated light and dark areas. For best results, a face should be illuminated by a uniform light from the front. Furthermore, differences in pose can affect characteristics of the image. For best results with matching, the individual should look directly at the camera. If an individual is looking in a different direction, the distances between facial features change due to differences in perspective. Generally, authentication systems provide more uniform images than for identification systems. The individuals are cooperative and can be directed to look directly at a camera with proper illumination for acquiring the images, both for the database and for the comparison image. Often, in an identification system, the subject is not cooperative and lighting conditions are poor. Therefore, a need exists for a system which allows modification of images to correct for differences in lighting or pose, in either identification systems or authentication systems.
A facial image is affected by coloring of the individual as well as by the shape of the individuals head. For improved reliability in comparisons, information about facial shape can be acquired as well as a two dimensional, color images. Three dimensional cameras are known and used in some systems for capturing images and making comparisons. With a three dimensional camera, shape information is acquired. With shape information, the images can be modified to remove differences in pose prior to comparison. However, three dimensional cameras are more expensive and more complicated than simple two dimensional cameras. Furthermore, a three dimensional camera generally requires a cooperative individual who maintains a single pose for sufficient time to acquire a proper image. Therefore, a need exists for a system which utilizes shape information for making facial image comparisons without the need for a three dimensional camera.